Dataset Information

A Bottom-Up Approach for Developing Aptasensors for Abused Drugs: Biosensors in Forensics.

ABSTRACT: Aptamer-based point-of-care (POC) diagnostics platforms may be of substantial benefit in forensic analysis as they provide rapid, sensitive, user-friendly, and selective analysis tools for detection. Aptasensors have not yet been adapted commercially. However, the significance of the applications of aptasensors in the literature exceeded their potential. Herein, in this review, a bottom-up approach is followed to describe the aptasensor development and application procedure, starting from the synthesis of the corresponding aptamer sequence for the selected analyte to creating a smart surface for the sensitive detection of the molecule of interest. Optical and electrochemical biosensing platforms, which are designed with aptamers as recognition molecules, detecting abused drugs are critically reviewed, and existing and possible applications of different designs are discussed. Several potential disciplines in which aptamer-based biosensing technology can be of greatest value, including forensic drug analysis and biological evidence, are then highlighted to encourage researchers to focus on developing aptasensors in these specific areas.

SUBMITTER: Aydindogan E

PROVIDER: S-EPMC6955935 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

A Bottom-Up Approach for Developing Aptasensors for Abused Drugs: Biosensors in Forensics.

Celikbas Eda E Balaban Simge S Evran Serap S Coskunol Hakan H Timur Suna S

Biosensors 20191001 4

Aptamer-based point-of-care (POC) diagnostics platforms may be of substantial benefit in forensic analysis as they provide rapid, sensitive, user-friendly, and selective analysis tools for detection. Aptasensors have not yet been adapted commercially. However, the significance of the applications of aptasensors in the literature exceeded their potential. Herein, in this review, a bottom-up approach is followed to describe the aptasensor development and application procedure, starting from the sy ...[more]

PMID: 31581533

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Project description:Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

Dataset Information

A Bottom-Up Approach for Developing Aptasensors for Abused Drugs: Biosensors in Forensics.

Publications

A Bottom-Up Approach for Developing Aptasensors for Abused Drugs: Biosensors in Forensics.

Similar Datasets

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